o_19k6fnuqr4ap1kbjthf1mug1eigh.pdf

Brain and Cognition xxx (2011) xxx–xxx 

Contents lists available at ScienceDirect 

Brain and Cognition 

journal homepage: www.elsevier.com/locate/b&c 

Emotions induced by operatic music: Psychophysiological effects of music, plot, 

and acting 

A scientist’s tribute to Maria Callas 

Felicia Rodica Baltesß, Julia Avram, Mircea Miclea, Andrei C. Miu ⇑ 

Emotion and Cognition Neuroscience Laboratory, Department of Psychology, Babes-Bolyai University, Cluj-Napoca, CJ 400015, Romania 

article 

info 

abstract 

Article history: 

Accepted 31 January 2011 

Available online xxxx 

Keywords: 

Operatic music 

Music-induced emotions 

Physiological differentiation of emotions 

Operatic music involves both singing and acting (as well as rich audiovisual background arising from the 

orchestra and elaborate scenery and costumes) that multiply the mechanisms by which emotions are 

induced in listeners. The present study investigated the effects of music, plot, and acting performance 

on emotions induced by opera. There were three experimental conditions: (1) participants listened to 

a musically complex and dramatically coherent excerpt from Tosca; (2) they read a summary of the plot 

and listened to the same musical excerpt again; and (3) they re-listened to music while they watched the 

subtitled film of this acting performance. In addition, a control condition was included, in which an independent 

sample of participants succesively listened three times to the same musical excerpt. We measured 

subjective changes using both dimensional, and specific music-induced emotion questionnaires. 

Cardiovascular, electrodermal, and respiratory responses were also recorded, and the participants kept 

track of their musical chills. Music listening alone elicited positive emotion and autonomic arousal, seen 

in faster heart rate, but slower respiration rate and reduced skin conductance. Knowing the (sad) plot 

while listening to the music a second time reduced positive emotions (peacefulness, joyful activation), 

and increased negative ones (sadness), while high autonomic arousal was maintained. Watching the acting 

performance increased emotional arousal and changed its valence again (from less positive/sad to 

transcendent), in the context of continued high autonomic arousal. The repeated exposure to music 

did not by itself induce this pattern of modifications. These results indicate that the multiple musical 

and dramatic means involved in operatic performance specifically contribute to the genesis of musicinduced 

emotions and their physiological correlates. 

Ó 2011 Elsevier Inc. All rights reserved. 

‘‘Maria Callas exploded the concept of what beautiful singing 

means: Is it pretty sounds and pure tones? Or should beauty 

evolve from text, musical shape, dramatic intent and, especially, 

emotional truth?’’ 

(Anthony Tommassini in ‘‘A Voice and a Legend That Still Fascinate; 

Callas Is What Opera Should Be’’, The New York Times, September 

15, 1997) 

Abbreviations: DBP, diastolic blood pressure; ECG, electrocardiogram; GEMS, 

Geneva Emotional Music Scale; HF-HRV, power in the high frequency band of HRV; 

HR, heart rate; HRV, heart rate variability; IBI, cardiac interbeat intervals; LF-HRV, 

power in the low frequency band of HRV; NA, negative affect; PA, positive affect; 

PANAS, Positive and Negative Affect Schedule; RR, respiratory rate; RSA, respiratory 

sinus arrhythmia; SAM, Self-Assessment Manikin; SBP, systolic blood pressure; SCL, 

skin conductance level; SEM, standard error of the mean; VLF-HRV, power in the 

very low frequency band of HRV. 

⇑ Corresponding author. Address: 37 Republicii, Cluj-Napoca, CJ 400015, 

Romania. Fax: +40 264 590967. 

E-mail address: andreimiu@gmail.com (A.C. Miu). 

1. Introduction 

We are often emotionally moved by musical performances. 

However, emotions induced by music have only recently drawn 

the attention of scholars in cognitive and affective sciences (Juslin 

& Vastfjall, 2008; Scherer & Zentner, 2001). Field studies have 

confirmed that music pervades everyday life and some of its most 

important functions are related to mood change and emotion regulation 

(DeNora, 1999; Juslin, Liljestrom, Vastfjall, Barradas, & 

Silva, 2008; Sloboda & O’Neil, 2001). In daily life, music generally 

increases positive affect, alertness, and focus in the present 

(Sloboda, O’Neil, & Ivaldi, 2001). In addition, it provides opportunities 

for venting strong emotions, increasing their intensity, or 

calming down (DeNora, 1999). Therefore, music has been related 

to the genesis and control of emotions. 

Despite previous debates on whether music induces emotions in 

listeners (i.e., the so-called ‘‘emotivist’’ position), or only expresses 

emotions that listeners can recognize (i.e., the ‘‘cognitivist’’ 

0278-2626/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. 

doi:10.1016/j.bandc.2011.01.012 

Please cite this article in press as: Baltesß, F. R., et al. Emotions induced by operatic music: Psychophysiological effects of music, plot, and acting. Brain and 

Cognition (2011), doi:10.1016/j.bandc.2011.01.012

2 F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 

position) (Kivy, 1990; Scherer & Zentner, 2001), the recent literature 

has generally supported the former view that music induces 

subjective (e.g., self-reported sadness), behavioral (e.g., crying), 

and physiological changes (e.g., heart rate [HR – see list of acronyms] 

deceleration) that are characteristic of emotions (Bharucha, 

Curtis, & Paroo, 2006; Juslin & Vastfjall, 2008; Koelsch, 2005; 

Scherer & Zentner, 2001). In addition, the mechanisms by which 

music induces emotions (e.g., semantic associations, emotional 

contagion based on observation of facial and vocal expressions; 

see Bezdek & Gerrig, 2008; Hietanen, Surakka, & Linnankoski, 

1998; Lundqvist & Dimberg, 1995) may not be specific to music, 

but this possibility has only recently started to be investigated 

(for reviews, see Juslin & Vastfjall, 2008; Scherer & Zentner, 

2001). The present report stems from the emotivist approach, 

and will examine the effects of opera on listeners’ physiological responses 

and subjective ratings of their own emotions. 

One way to investigate these issues has been to identify physiological 

responses during music listening (e.g., Krumhansl, 1997; 

Nyklícek, Thayer, & Van Doornen, 1997). This approach has extended 

the studies on the physiological differentiation of emotions 

induced by facial expressions (e.g., Ekman, Levenson, & Friesen, 

1983), images (e.g., Codispoti, Bradley, & Lang, 2001), and even natural 

sounds (e.g., Bradley & Lang, 2000). Previous studies indicated 

that only certain emotions (e.g., fear, disgust) can be distinguished 

based on their autonomic signatures (for review see Levenson, 

1992), but the effect sizes were small or medium at best (Cacioppo, 

Berntsen, Klein, & Poehlmann, 1997). These findings are not surprising 

considering the limited emotional saliency of images and 

words presented in laboratory settings. Recent psychophysiological 

studies have used more complex stimuli such as films, and consequently 

induced more robust experiences of emotion and 

physiological responses (e.g., Frazier, Strauss, & Steinhauer, 2004; 

Kreibig, Wilhelm, Roth, & Gross, 2007). 

1.1. Psychophysiology of music-induced emotions 

Like films, music has been shown to produce physiological 

changes that can distinguish between emotions. In two landmark 

studies, Krumhansl (1997), and Nyklícek et al. (1997) measured a 

large array of cardiovascular, respiratory, and electrodermal responses 

in association with self-report measures of emotions induced 

by music. Emotions were differentiated based on certain 

physiological responses such as respiratory sinus arrhythmia 

(RSA) and cardiac interbeat intervals (IBI) (Nyklícek et al., 1997). 

For instance, sadness ratings correlated positively with IBI, systolic 

(SBP) and diastolic blood pressure (DBP), and negatively with skin 

conductance level (SCL) (Khalfa, Peretz, Blondin, & Manon, 2002; 

Krumhansl, 1997). Emotional arousal was best explained by physiological 

changes, which accounted for 62.5% of the variance 

(Nyklícek et al., 1997). There is only one psychophysiological field 

study that measured emotional ratings, electrodermal and respiratory 

responses in a sample of spectators (i.e., 27 listeners) during 

several live performances of Wagner’s operas given in the festival 

theater of Bayreuth in 1987–1988 (Vaitl, Vehrs, & Sternagel, 

1993) 1 . In contrast to laboratory studies, these limited field results 

suggested that physiological responses differed between opera leitmotivs, 

but there was a weak correspondence between physiological 

and subjective measures of emotions. 

Psychophysiological studies have thus focused on the coherence 

between subjective, behavioral, and physiological components of 

music-induced emotions. Lundqvist, Carlsson, and Juslin (2009) reported 

an association between music-induced happiness and 

1 A recent laboratory study on psychophysiological changes induced by opera came 

to our attention while this article was under review. See Bernardi et al. (2009). 

greater SCL, and supported the emotivist position. In contrast, another 

study found that increased emotional arousal occurred without 

changes in SCL (Grewe, Nagel, Kopiez, & Altenmuller, 2007a). 

The latter pattern of results was interpreted as evidence for the 

cognitivist position, although the participants were clearly instructed 

to rate the emotional arousal they felt, and not that expressed 

by the music. These apparently divergent results might 

be explained by methodological differences, considering that one 

study used a self-report instrument that measured changes in several 

basic emotions (Lundqvist et al., 2009), and the other measured 

changes in arousal and valence across emotions (Grewe 

et al., 2007a). In addition, there are emotions specifically induced 

by music that are not captured by basic emotion measures such 

as the one used by Lundqvist et al. (2009). 

1.2. Specific music-induced emotions 

It has been argued that aesthetic emotions are deeper and more 

significant (Sloboda, 1992), nuanced and subtle (Scherer & Zentner, 

2001) than other more general emotions. Indeed, the range of music-induced 

emotions goes beyond the emotions captured by the 

basic emotion models. A recent field study showed that a nine-factor 

model best fitted the emotion descriptors that were chosen by 

music listeners who attended a classical music festival (Zentner, 

Grandjean, & Scherer, 2008). It included emotion categories (e.g., 

wonder, transcendence) that are not part of any current model of 

emotion. The Geneva Emotional Music Scale (GEMS) is the first 

questionnaire designed to measure music-induced emotions 

(Zentner et al., 2008). To our knowledge, no study has investigated 

the correlation between physiological responses and music-induced 

emotions measured by GEMS. 

1.3. Music-induced chills 

Music-induced emotions are often accompanied by physical 

sensations such as chills (i.e., tremor or tingling sensations passing 

through the body as the result of sudden keen emotion or excitement). 

Two landmark studies indicated that the great majority of 

people were susceptible to chills (Sloboda, 1991), and these bodily 

phenomena were associated with music-induced emotions, especially 

sadness and melancholy (Panksepp, 1995). Musical events 

such as crescendos or a solo instrument (e.g., a soprano’s voice) 

emerging from a softer orchestral background induced chills 

(Grewe, Nagel, Kopiez, & Altenmuller, 2007b; Panksepp, 1995). 

Psychophysiological studies have shown that music-induced chills 

correlated with increases in SCL and HR (Grewe et al., 2007b; 

Rickard, 2004). The present study aims to integrate the measurement 

of chills, music-induced emotions reflected by GEMS, and a 

wider range of physiological changes. 

1.4. The duration of musical stimuli 

One important aspect that differentiates studies of music-induced 

emotions is the duration of stimuli. For instance, many studies 

used short (i.e., several seconds), monotonic musical stimuli. It 

has been suggested that even less than one second of music is sufficient 

to prime an emotional meaning (e.g., Bigand, Vieillard, 

Madurell, Marozeau, & Dacquet, 2005; Peretz, Blood, Penhune, & 

Zatorre, 2001; Watt & Ash, 1998). However, this approach has at 

least two limitations. First, it usually involves forced-choice responses 

that increase the difficulty of emotional valence processing 

(Bigand et al., 2005; Peretz et al., 2001). Second, the correct 

categorization of the emotional content of music may only reflect 

the emotions that listeners perceive in music. One second may 

not be enough time to develop an emotional response. At any rate, 

longer durations of musical stimuli increase the magnitude of 



F.R. Baltesß et al. / Brain and Cognition xxx (2011) xxx–xxx 3 

psychophysiological responses in music-induced emotions (Witvliet 

& Vrana, 2007). Psychophysiological studies generally used longer 

stimuli (i.e., ranging from 6 to 600 s), and it has been argued that 

the use of full music pieces has greater external validity when 

investigating emotional responses to music (Grewe et al., 2007a; 

Nater, Abbruzzese, Krebs, & Ehlert, 2006; Rickard, 2004). 

1.5. Multiple sources of emotion in operatic music 

The duration of musical stimuli, as well as the integration of 

music with congruent visual and verbal cues are important contributors 

to emotional responses that people develop to musical 

performance (Bezdek & Gerrig, 2008; Scherer & Zentner, 2001). 

Operatic music performance involves both singing and acting, 

which multiplies the mechanisms by which emotions are induced 

in listeners. Opera adds the power of the dramatic plot and the personality 

of the performer to the affective message of the musical 

score and the emotional expressivity of voice (Scherer, 1995). 

The rich audiovisual background arising from the orchestra and 

elaborate scenery and costumes are also important. The objective 

of the present study was to investigate for the first time the cumulative 

contributions of music listening, learning the context of the 

events it portrays (i.e., plot), and watching the acting performance 

to emotions induced by opera. 

These sources may support the genesis of emotion either independently 

or in concert. Research on film music supports the latter 

possibility. For instance, music presented during the opening scene 

of a film influenced the emotional valence of words that participants 

used in their continuations of the narratives (Vitouch, 

2001). In addition, judgments of characters displaying neutral 

emotions were significantly affected by the emotional content of 

the music that accompanied the film (Tan, Spackman, & Bezdek, 

2007). Lyrics are also important in emotional responses to music. 

For instance, the emotional effects of music and lyrics were investigated 

by combining musical excerpts with lyrics that conveyed 

the same emotion or another emotion (Ali & Peynircioglu, 2006; 

Stratton & Zalanowski, 1994). These studies indicated that lyrics 

enhanced emotion in sad and angry music. Furthermore, these 

emotions readily transferred to images that were arbitrarily associated 

with songs (Ali & Peynircioglu, 2006). In addition, visual 

cues such as facial expressions are preattentively integrated with 

vocal cues and influence the emotional judgment of the latter (de 

Gelder, Bocker, Tuomainen, Hensen, & Vroomen, 1999). Therefore, 

it seems likely that facial expressions of singers influence the emotional 

processing of music. Overall, music, lyrics, and visual cues 

seem to significantly contribute to the genesis of music-induced 

emotions, and their concerted contribution may explain why operatic 

music is so effective in inducing emotions. However, this complex 

issue has not been investigated to date. 

1.6. Objectives of the present study 

We investigated subjective and physiological emotional responses 

to operatic music. In order to maximize external validity, 

we chose a dramatically coherent and musically complex excerpt 

from Tosca by Giacomo Puccini. The soprano Maria Callas and the 

baritone Tito Gobbi gave a legendary interpretation of the main 

characters in Tosca, and their 1964 live performance at Covent Garden 

was fortunately recorded on film. In this performance, both artists 

impress by their emotional identification with the characters, 

and the way they deliver the mixture of lust and hate, fear, emotional 

vulnerability and indignation through their voice (Huck, 

1984). Studying the psychophysiology of emotion during this performance 

offers us an opportunity to catch a scientific glimpse of 

the emotional force that artists such as Maria Callas have inspired. 

The present study had three experimental conditions that 

investigated the contributions of music, plot, and acting performance 

to emotional responses. First, participants listened to the 

musical excerpt. Then, they read a summary of the plot and listened 

to the same musical excerpt again. In the third condition, 

they re-listened to music while they watched the subtitled film 

of this acting performance. In between conditions, we measured 

music-induced emotions using both dimensional, and specific music-induced 

emotion questionnaires. During the experimental conditions, 

cardiovascular, electrodermal and respiratory responses 

were continuously recorded, and the participants kept track of 

their musical chills. 

Since there are very few psychophysiological studies of emotions 

in operatic music (and operatic music is so diverse), the present 

study was consequently exploratory. Based on the musical and 

dramatic content of this musical excerpt, we expected that it 

would induce a pattern of emotions characterized by increased 

unpleasant emotions (e.g., sadness) and decreased pleasant emotions 

(e.g., joyful activation, peacefulness). In addition, based on 

the literature in related areas (e.g., sadness induced by films), we 

expected a change in the sympathovagal balance, with vagal withdrawal 

and sympathetic activation, as well as decreases of SCL and 

respiratory rate (RR). We were specifically interested in the way 

each successive layer of complexity influenced music-induced 

emotions and their physiological correlates. 

2. Methods 

2.1. Participants 

N = 37 healthy, right-handed Romanian volunteers (25 women; 

mean age = 21.4 years, ranging between 19 and 24 years), with 

good hearing, were selected for this study (out of an initial pool 

of 45 volunteers). The sample size was determined by using a priori 

statistical power analysis (power = 0.95; alpha = 0.05; effect 

size f = 0.25) run in the G-Power 3.1 software (Faul, Erdfelder, Lang, 

& Buchner, 2007). The participants had no significant musical education, 

but they reported that music was an important part of their 

lives. None of the participants reported having listened to Tosca before, 

a preference for classic or operatic music, or understood Italian. 

These inclusion criteria were important in order to control for 

the degree of familiarity with the selected musical piece, and 

understanding of the lyrics. None of the participants reported cardiovascular 

or neurological problems, or any kind of medical treatment 

that would interfere with cardiovascular and autonomic 

functions. Participants were asked to refrain from alcohol, caffeine 

and smoking at least four hours before the experiment. All the participants 

signed an informed consent to participate to the experiment 

and the procedures complied with the recommendations of 

the Declaration of Helsinki for human studies. 

2.2. Materials 

We used an excerpt from Giacomo Puccini’s Tosca (Act II), filmed 

at Covent Garden in 1964, starring Maria Callas as Floria Tosca, Tito 

Gobbi as Scarpia, and Renato Cioni as Mario Cavaradossi (Zeffirelli, 

2002). We selected and juxtaposed two excerpts (i.e., excerpt 1 from 

11 0 :00 00 [Scarpia: Ed or fra noi parliam da buoni amici]to22 0 :31 00 [Scarpia: 

Io? Voi!], and excerpt 2 from 23 0 :36 00 [Tosca: Quanto?]to31 0 :35 00 

[Tosca: Perché me ne rimuneri cosi?]) for the following reasons. First, 

these excerpts contain the plot (see Supplementary materials) 

involving all the three main characters (i.e., Tosca, Scarpia, and Cavaradossi). 

Second, these excerpts are musically and dramatically 

heterogenous, with a variety of rhythmical dynamics, ascending 

and descending scales, large vocal range and emotional tension. In 




addition, our approach to inducing music-related emotions explicitly 

relied on using longer excerpts (e.g., 19 0 :30 00 in the present study) 

from popular operatic compositions in order to credibly replicate the 

musical context that induces emotions in the real world (Grewe 

et al., 2007a; Juslin & Vastfjall, 2008; Rickard, 2004). Music was presented 

using Technics RP-F600 high-quality noise canceling closed 

headphones. Before the start of the experiment, a test tone was 

played, giving participants the opportunity to adjust the loudness 

to an individually comfortable level. After the participants read the 

plot before the second experimental condition, the experimenters 

checked how well the plot was understood by asking the participants 

the following questions: (1) who are the main characters; (2) 

what happens in this opera; and (3) what happens in this excerpt 

of the opera? The great majority of the participants answered correctly 

to these questions, but those who omitted or were not sure 

of certain details were allowed to read the summary of the plot again 

and assisted with supplementary explanations by the experimenters. 

This experimental condition started only after each participant 

correctly answered all the questions regarding the plot. The video 

was displayed on a Samsung SyncMaster 205BW monitor 

(50.8 cm), located 1.5 m in front of the participant’s chair. The experimental 

room was small and dimly lit, and was maintained at a comfortable 

ambient temperature. 

2.3. Procedure 

There were three conditions of musical experience: (1) music 

listening; (2) music re-listening after learning the plot; and (3) music 

re-listening while watching the acting performance. Previous 

studies revealed that the psychophysiological responses induced 

by music are not significantly affected by repeated exposure 

(Grewe et al., 2007a, 2007b). However, we also included a control 

condition in which an independent sample of N = 9 participants 

(five women) successively listened three times to the same musical 

excerpt, in order to check whether the repeated exposure to music 

influenced the subjective and physiological measures. The same 

questionnaires and physiological recordings were used in the main 

experiment and the supplementary control condition, except SBP 

and DBP that were not measured in the latter condition. The participants 

in this control experiment met all the inclusion criteria that 

applied to the main experiment. 

At the arrival to the laboratory, each participant completed the 

general scales of the Positive and Negative Affect Schedule (PANAS- 

I) (Watson & Clark, 1994), in order to control for differences in 

affective mood before the start of the experiment. After a habituation 

period during which participants were explained that several 

non-invasive recordings will be taken during music listening, the 

physiological electrodes for SCL and electrocardiogram (ECG), as 

well as the respiration transducer and an arm cuff coupled to an 

automatic blood pressure monitor were attached. Participants 

were instructed to sit comfortably and relax, and carefully listen 

to the music while monitoring the music-related emotions they 

felt without trying to control them in any way. They were instructed 

to identify emotions they felt during music listening, 

and not emotions that the music expressed. They were also requested 

to keep a count on a scratch sheet of the number of chills 

they experienced during each condition. 

Each condition was preceded by a 5 min interval during which 

baseline physiological recordings were made. Participants completed 

each condition and unless they wanted a break, they moved 

onto the following condition. First, they listened to the musical excerpt. 

In the second condition, they were given a summary of the 

plot (see Supplementary materials). Using a brief questionnaire, 

the experimenters first made sure that participants understood 

the plot and knew the characters, and then music was played 

again. In the third condition, the participants listened to music 

while also watching the acting performance. In order to facilitate 

the complete understanding of the plot and acting performance, 

the movie was subtitled in Romanian. 

After each condition, participants were required to rate the 

emotional arousal (1 – non-arousing to 5 – arousing) and valence 

(1 – unpleasant to 5 – pleasant) induced by music; and completed 

GEMS (Zentner et al., 2008) for music-induced emotions. 

2.4. Self-report measures 

The positive (PA) and negative affect (NA) scales of PANAS-I 

(Watson & Clark, 1994) include 20 items each, which measure 

the affective mood in the past few weeks until present. Emotional 

arousal and valence were measured using the Self-Assessment 

Manikin (SAM) (Bradley & Lang, 1994). SAM is a non-verbal pictorial 

assessment technique that directly measures the pleasure and 

arousal (as well as dominance, which was not used in the present 

study) associated with a person’s affective reaction to a wide variety 

of stimuli. For the measurement of emotions induced by music 

(e.g., wonder, transcendence, tenderness, peacefulness), we used 

the long (i.e., 45 items) variant of GEMS (Zentner et al., 2008). 

GEMS scores are grouped on nine factors: wonder; transcendence; 

tenderness; nostalgia; peacefulness; power; joyful activation; tension; 

and sadness. Whereas the dimensional rating allowed us to 

document general changes of emotional arousal and valence, GEMS 

offered us the possibility of actually identifying the specific emotions 

that were induced by each experimental condition. Self-reports 

of chills were also collected. 

2.5. Physiological measures 

ECG, SCL, and respiration were continuously recorded during 

the baseline and experimental conditions, using a BIOPAC MP150 

system and specific electrodes and transducers. Blood pressure 

was intermittently measured at fixed intervals during the experimental 

condition. 

2.5.1. Cardiovascular measures 

ECG was recorded using disposable pregelled Ag/AgCl electrodes 

placed in a modified lead II configuration, at a sample rate of 500 

samples/s, and amplified using an ECG100C module. After visual 

inspection of the recordings and editing to exclude artifacts in 

AcqKnowledge 3.9.0.17, all the recordings were analyzed using Nevrokard 

7.0.1 (Intellectual Services, Ljubljana, Slovenia). We calculated 

HR, and HR variability (HRV) indices in the time and 

frequency domains: mean IBI between successive R waves (HR and 

IBI are negatively correlated); power in the high frequency 

(HF-HRV) band (0.15–0.4 Hz in adults) of HRV, also known as 

RSA; power in the low (LF-HRV) (0.05–0.15 Hz), and very low 

frequency (VLF-HRV) (0–0.05 Hz) bands of HRV, as well as LF/HF 

ratios. The latter three measures, obtained by spectral analysis, are 

reported in normalized units (see Task Force Report, 1996). RSA 

reflects vagal modulation of the heart, whereas LF-HRV reflects a 

complex interplay between sympathetic and vagal influences (see 

Eckberg, 1997; Kingwell et al., 1994; Miu, Heilman, & Miclea, 

2009; Task Force of the European Society of Cardiology and Electrophysiology, 

1996). These measures were derived from each baseline 

and experimental conditions. The statistical analyses of RSA included 

respiration frequency as covariate in order to control for 

the influence of respiration on this measure. Therefore, the results 

reported here controlled for the influence of respiration on RSA. 

2.5.2. Skin conductance 

After cleaning and abrading the skin of the palms, TSD203 

electrodermal response electrodes filled with isotonic gel were attached 

to the volar surfaces of the index and medius fingers. SCL 




recordings were amplified using a GSR100C module. We estimated 

SCL by extracting the area under the curve (lS/s) from each baseline 

and experimental condition, after the downdrift in the SCL 

waves was eliminated using the ‘‘difference’’ function of Acq- 

Knowledge, as described in (Bechara, Damasio, Damasio, & Lee, 

1999; Miu, Heilman, & Houser, 2008). 

2.5.3. Respiration 

One channel of respiration was measured using a top respiration 

band placed on the chest, below the breast. The data were recorded 

with the RSP100C module and the TSD201 Transducer of 

the Biopac system. TSD201 can arbitrarily measure slow to very 

fast thoracic and abdominal respiration patterns with no loss in 

signal amplitude, optimal linearity and minimal hystheresis. RR 

(in cycles per minute) was calculated breath by breath using Acq- 

Knowledge software. 

2.5.4. Blood pressure 

SBP and DBP (in millimeters of mercury) were measured intermittently 

with an automatic blood pressure monitor (Digital Blood 

Pressure monitor, Vital System) through an arm cuff at the participant’s 

right upper arm. Inflation was initiated at the end of the 

baseline, at minutes 5, 10, 15, and at the end of the musical 

condition. 

2.6. Data reduction 

For the continous physiological measurements (i.e., all except 

SBP and DBP), we calculated difference scores by subtracting each 

baseline measure (i.e., the quiet sitting period immediately preceding 

each musical experience condition) from the corresponding 

experimental condition measure (see Kreibig et al., 2007). In the 

case of SBP and DBP that were intermittently measured, we first 

calculated the arithmetic mean of the physiological data from 

baseline and experimental conditions, and then derived the same 

difference score. The raw scores were transformed to T scores for 

normalization. 

2.7. Statistical analysis 

Data were inspected for outliers (Stevens, 2002, pp. 14–17) – 

only 0.8% of the data were excluded. We used repeated measure 

ANOVA and ANCOVA, followed by post hoc tests, in order to determine 

whether there were differences in emotion experience and 

physiological responses between the musical experience conditions. 

Effect sizes for t-tests and AN/COVA are reported as Cohen’s 

d and g 2 p , and interpreted as follows: d = 0.2 or g2 p 

= 0.01 – small effect 

size; d = 0.5 or g 2 p 

= 0.059 – medium effect size; and d = 0.8 or 

g 2 p 

= 0.138 – large effect size (Cohen, 1988). We also used the Friedmann 

non-parametric test to analyze potential differences between 

the frequency of chills in the experimental conditions. In 

addition, correlation analyses allowed us to test the association between 

emotion experience, physiological responses, and chills. 

Simple regressions were used to test whether affective mood 

(i.e., PA and NA) predicted affect (i.e., dimensional and specific 

emotion ratings) and physiological responses. The data are reported 

in the graphs as means ± one standard error of the means 

(SEM). 

3. Results 

3.1. General affect 

A 3 (musical experience: music listening vs. learning the plot vs. 

watching the acting performance) 2 (sex: women vs. men) 

Fig. 1. Changes in emotional arousal and valence (SAM) induced by music listening 

(1), learning the plot (2), and watching the acting performance (3). 

ANCOVA indicated that musical experience had a significant main 

effect on self-reported emotional arousal (F[4, 32] = 6.19, p = 0.002, 

g 2 p 

= 0.12). NA and PA were included as covariates in these analyses 

in order to control for the affective mood of participants before the 

experiments. 

The analyses of the data from the supplementary control sample 

indicated that the repeated exposure to music had no significant 

effects on emotional arousal and valence (p= 0.3 for both) 

(see Supplementary Fig. 1). In addition, we compared the first music 

listening condition in the control experiment to the music listening 

condition from the main experiment, in order to verify 

their similarity. Indeed, there were no significant differences between 

the arousal (t[45] = 1.29, ns) and valence scores 

(t[45] = 1.23, ns) in the first conditions of the main and control 

experiments, respectively. 

Although emotional arousal and valence were not measured before 

the first condition because it would have been hard to find an 

equally complex, but emotionally neutral stimulus to which to 

compare the first experimental condition, we explored the affective 

experience that music listening induced by one sample Student t- 

tests. The expected mean was the mid-value of the SAM rating 

scale. These analyses indicated that music listening was associated 

with increased emotional arousal (t[35] = 2.42, p = 0.02, Cohen’s 

d= 0.3) and valence scores (t[35] = 8.57, p < 0.0001, Cohen’s d= 

1). Next, by comparing between the three experimental condition, 

we found that watching the acting performance significantly increased 

emotional arousal compared to learning the plot, and music 

listening (see Fig. 1). Neither the main effect of sex, nor the interaction 

of sex musical experience on emotional arousal and valence 

were statistically significant. 

3.2. Music-induced emotions 

The effects of musical experience and sex on music-induced 

emotions measured by GEMS were also investigated. A 3 (musical 

experience: music listening vs. learning the plot vs. watching the 

acting performance) 2 (sex: women vs. men) ANCOVA indicated 

that musical experience induced specific emotions. NA and PA 

were again included as covariates in these analyses. 



effects on any of the GEMS measures (p > 0.1 for all) (see 




decreased IBI (F[4, 32] = 2.98, p = 0.05, g 2 p 

= 0.08), and SCL 

(F[4, 32] = 3.2, p = 0.04, g 2 p 

= 0.09) in comparison to music listening. 

3.4. Experienced chills 

The repeated exposure of the independent control sample to 

music had no significant effect on self-reported chills (p = 0.3). 

There were no differences between the frequency of chills in the 

control and main experiments, respectively. 

A Friedman non-parametric test compared between the three 

experimental conditions in the main experiment and indicated 

that the exposure to the acting performance significantly increased 

the number of reported chills (v 2 = 8.92, p = 0.01) in comparison to 

learning the plot and music listening. 

3.5. Relationships between music-induced affect, chills, and 

physiological responses 

Fig. 2. Changes in GEMS scores induced by music listening (1), learning the plot (2), 

and watching the acting performance (3). 

Supplementary Fig. 2). We also compared the pattern of GEMS 

scores between the first conditions of the main and control experiments. 

There was only one significant difference on tenderness 

(t[45] = 2.25, p = 0.02), with higher scores in the music listening 

condition of the main experiment. 

By comparing between the three experimental condition, we 

found that learning the plot and watching the acting performance 

had significant effects on distinct music-induced emotions (see 

Fig. 2). On the one hand, learning the plot reduced the scores of 

peacefulness (F[4, 32] = 7.84, p = 0.0009, g 2 p 

= 0.23) and joyful activation 

(F[4, 32] = 5.85, p = 0.004, g 2 p 

= 0.17), and increased sadness 

(F[4, 32] = 10.98, p = 0.0001, g 2 p 

= 0.32). On the other hand, watching 

the acting performance increased the scores of wonder 

(F[4, 32] = 8.13, p = 0.0007, g 2 p 

= 0.23) and transcendence 

(F[4, 32] = 4.02, p = 0.02, g 2 p 

= 0.11). Neither the main effect of sex, 

nor the interaction of sex musical experience on specific emotions 

were statistically significant. 

3.3. Physiological responses 



effects on any of the physiological measures (p > 0.39 for all) 

(see Supplementary Fig. 3). However, a couple of physiological 

measures were significantly different between the first conditions 

of the main and control experiments: IBI (t[45] = 4.77, p < 0.0001) 

and RR (t[45] = 2.09, p = 0.04), with lower values in the first condition 

of the control experiment. 

There were significant main effects of musical experience on 

physiological responses. In comparison to baseline measures, music 

listening (i.e., the first condition) significantly decreased RR 

(F[4, 32] = 9.12, p = 0.005, g 2 p 

= 0.29), IBI (F[4, 32] = 3.11, p = 0.02, 

g 2 p = 0.09), and SCL (F[4, 32] = 29.76, p < 0.0001, g2 p 

= 0.75). In the 

following experimental conditions, both learning the plot, and 

watching the acting performance specifically influenced physiological 

measures (Fig. 3). On the one hand, learning the plot significantly 

decreased RSA (F[4, 32] = 3.05, p = 0.05, g 2 p 

= 0.08) and 

increased LF-HRV (F[4, 32] = 3.49, p = 0.03, g 2 p 

= 0.09) and LF/HF 

(F[4, 32] = 3.77, p = 0.02, g 2 p 

= 0.1) in comparison to music listening. 

On the other hand, watching the acting performance significantly 

We analyzed the correlations between emotions, chills, and 

physiological responses within each musical experience condition. 

The following paragraph reports the main patterns of correlations 

for which we had a priori hypotheses (for detailed results, see 

Tables 1–3). These analyses indicated that LF-HRV positively, and 

RSA negatively correlated with emotional arousal after learning 

the plot. In the same condition, the frequency of chills also correlated 

with arousal. In contrast, RR positively correlated with emotional 

valence (i.e., increased RR for positive valence) during music 

listening. 

The analyses of music-induced emotions showed that LF-HRV 

positively, and RSA negatively correlated with the level of wonder, 

power, and joyful activation after learning the plot. Also, LF-HRV 

positively and RSA negatively correlated with the frequency of 

chills both after learning the plot, and while watching the acting 

performance. Chills consistently correlated positively with the levels 

of wonder and transcendence in all three musical experience 

conditions. We also checked if this correlation was replicated in 

the control experiment and we confirmed that chills correlated significantly 

with wonder (r = 0.65, p = 0.05) and marginally with 

transcendence (r = 0.6, p = 0.08). Another consistent pattern of positive 

correlations was that between RR, wonder (during all three 

musical experience conditions), and transcendence (during music 

listening, and watching the acting performance). 

3.6. Previous mood and music-induced affect 

PA and NA significantly correlated (r = 0.45, p < 0.01), but the 

low correlation allowed us to use both as predictors (i.e., negligible 

multicollinearity). Our hypotheses were that NA would positively 

predict unpleasant emotions measured by GEMS (i.e., nostalgia, 

sadness, tension), and negatively predict pleasant emotions (i.e., 

wonder, transcendence, power, tenderness, peacefulness, joyful 

activation). We also expected that PA would negatively predict 

unpleasant emotions and positively predict pleasant emotions. In 

addition, based on the work of Panksepp (1995), we also hypothesized 

that NA would negatively predict chills and RSA. On the 

assumption that only the first condition (i.e., music listening) 

would be directly affected by previous mood, regression analyses 

were run on music-induced emotions and chills recorded during 

the first condition. The results indicated that power (R = 0.53, 

p = 0.0009, g 2 p 

= 0.28) and joyful activation (R = 0.45, p = 0.05, 

g 2 p 

= 0.21) were negatively predicted by NA. In contrast, PA positively 

predicted power (R = 0.51, p < 0.001, g 2 p 

= 0.26) and joyful 

activation (R = 0.38, p = 0.02, g 2 p = 0.15). 




Fig. 3. Changes in interbeat intervals (IBI), heart rate (HR), power in the very low frequency (VLF), and low frequency (LF) bands of heart rate variability, respiratory sinus 

arrhythmia (RSA), sympathovagal balance (LF/HF), skin conductance level (SCL), systolic blood pressure (SBP), diastolic blood pressure (DBP), and respiratory rate (RR) 

induced by music listening (1), learning the plot (2), and watching the acting performance (3). 

4. Discussion 

The results of this study confirmed that music listening, learning 

the plot, and watching the acting performance had specific effects 

on emotional responses measured at the subjective and 

physiological levels. 

4.1. Effects of music, plot and acting 

In comparison to expected mean scores, music listening increased, 

as one would expect, emotional arousal and valence. In 

addition, music listening decreased RR, IBI and SCL, in comparison 

to baseline physiology. These results seem to extend previous 

observations that sad music is associated with decreased SCL, 

and sadness induced by music is well discriminated by respiratory 

changes (Krumhansl, 1997; Nyklícek et al., 1997). Moreover, our 

observation of decreased SCL associated with this music excerpt 

is also in line with studies that induced sadness by directed facial 

action tasks (Ekman et al., 1983; Levenson, 1992). 

It may seem that the pattern of reduced RR and SCL, and increased 

HR (i.e., decreased IBI) in the music listening condition is 

contradictory. Early observations indicated that the minor tonalities 

of music increased HR (Hyde & Scalapino, 1918), whereas 

the tempo of music influenced RR (Diserens, 1920). Bernardi and 

colleagues (2009) have recently reported that music crescendos 

or emphases (e.g., in Nessun dorma from Puccini’s Turandot) induced 

skin vasoconstriction along with increases in blood pressures 

and HR. There was also increased breath depth during 

music crescendos, but these modulations of respiratory power 

were independent of cardiovascular modulations. The present 

study also shows that music listening independently modulated 

RR and HR, and the former correlated with negative valence, wonder 

and transcendence. Also in line with the present results, Nakahara, 

Furuya, Francis, & Kinoshita, (2010) found that playing Bach’s 

No. 1 Prelude with emotional expression increased HR and decreased 

RR in pianists, in comparison to playing the same piece 

without emotional expression. Therefore, these studies suggest 

that music-induced emotions can independently modulate cardiovascular 

and respiratory activities, and this pattern of physiological 

changes may contribute to the receptiveness or arousal to music 

(Bernardi et al., 2009; the present study) and the capacity of 

performers to incorporate expressiveness in their performance 

(Nakahara, Furuya, Francis, & Kinoshita, 2010). 

Our control analyses on the data from an independent sample 

indicated that re-listening to the musical excerpt for three times 

did not increase emotional arousal and valence, or induced additional 

physiological changes by itself. Whereas there were no differences 

between the conditions of the control experiment, 

which argued that repeated music listening alone did not affected 

the subjective and physiological measurements, the relevance of 

the physiological measurements from the control experiment is 

limited. There were differences in IBI and RR between the sample 

used in the main and control experiments, respectively. This was 

probably due to the reduced sample size in the control experiment 

(N = 9, in comparison to N = 37 in the main experiment). Overall, 

the control data supported the view that the changes observed in 

the main experiment were not due to repeated music listening 

alone, although this inference should be taken with caution in regard 

to some of the physiological results. Replicating the control 

findings with a sample size that is similar to that of the main 

experiment would be necessary in order to unequivocally confirm 

that the repeated music listening alone does not change physiological 

activity. 

Learning the plot before listening to the musical excerpt the 

second time (in the main experiment) induced a pattern of emotional 

changes that included reduced peacefulness, joyful activation, 

and increased sadness. At the physiological level, learning 

the plot decreased RSA and increased LF-HRV. The change in RSA 

reflects vagal suppression that has been associated with negative 

emotional states and traits, such as anxiety and depression (Bleil, 

Gianaros, Jennings, Flory, & Manuck, 2008; Miu et al., 2009). The 

summary of the plot that the participants read before they 




Table 1 

Correlations between physiological responses, chills, and affect during music listening. 

Geneva Emotional Music Scale Chills 

Self-Assessment 

Manikin 

Sadness Tension 

Arousal Valence Wonder Transcendence Power Tenderness Nostalgia Peacefulness Joyful 

activation 

Systolic blood pressure (SBP) 0.23 0.12 0.23 0.36 * 0.34 * 0.13 0.29 0.03 0.17 0.3 0.07 0.09 

Diastolic blood pressure (DBP) 0.06 0.17 0.13 0.16 0.15 0.06 0.02 0.11 0.15 0.15 0.03 0.11 

Skin conductance level (SCL) 0.08 0.12 0.05 0.15 0.14 0.12 0.14 0.01 0.02 0.15 0.07 0.11 

Respiratory rate (RR) 0.01 0.4 * 0.35 * 0.35 * 0.7 0.23 0.32 0.08 0.12 0.04 0.00 0.27 

Cardiac interbeat intervals (IBI) 0.05 0.11 0.17 0.01 0.21 0.01 0.15 0.01 0.02 0.1 0.02 0.21 

Heart rate (HR) 0.04 0.08 0.14 0.01 0.18 0.03 0.12 0.02 0.04 0.11 0.06 0.18 

Power in the very low frequency of heart rate variability (VLF-HRV) 0.21 0.31 0.07 0.02 0.6 0.36 * 0.11 0.45 ** 0.07 0.1 0.08 0.03 

Power in the low frequency of heart rate variability (LF-HRV) 0.1 0.05 0.003 0.09 0.7 0.03 0.29 0.13 0.21 0.11 0.09 0.04 

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.02 0.01 0.07 0.05 0.01 0.07 0.27 0.16 0.25 0.13 0.04 0.15 

Ratio between low and high frequency powers of heart rate variability 0.15 0.15 0.19 0.07 0.16 0.09 0.22 0.15 0.1 0.00 0.04 0.05 

(LF/HF) 

Chills 0.22 0.08 0.44 ** 0.46 ** 0.11 0.00 0.19 0.12 0.12 0.1 0.26 

p 6 0.05. 

p 6 0.01. 

* 

** 

re-listened to the musical excerpt described negative emotional 

events (e.g., Scarpia tortures Cavaradossi and harasses Tosca; see 

Supplementary materials). Therefore, we argue that the sadness induced 

by learning the plot triggered vagal suppression that was 

neither explained by concomitant respiratory changes (i.e., RR 

was controlled for in the analyses of RSA), nor by re-listening to 

the musical excerpt by itself. The increase in LF-HRV suggests that 

learning the plot also facilitated sympathetic activity. However, LF 

probably reflects a complex interplay between sympathetic and 

vagal influences on the heart (Eckberg, 1997; Miu et al., 2009), so 

the effect of learning the plot on sympathetic activity should be taken 

with caution. Overall, learning the plot significantly influenced 

music-induced emotions and changed sympathovagal balance in 

the direction of greater preparedness for action. 

Watching the acting performance increased emotional arousal 

and valence (SAM) compared to the first two experimental conditions. 

Furthermore, it increased wonder and transcendence 

(GEMS). Notably, wonder and transcendence are emotions that 

are specifically induced by music (Zentner et al., 2008). In comparison 

to music listening and learning the plot, watching the acting 

performance added social-emotional and visuospatial cues to the 

musical experience: facial expressions, gestures and postures, 

translated lines, and scenery. These factors probably contributed 

to the semantic processing of music and vocal expressions, and 

we argue that this experimental condition best approximated the 

full musical experience of listeners attending a live opera performance. 

Watching the acting performance decreased IBI and SCL 

in comparison to music listening. Previous studies reported that 

music-induced sadness ratings correlated positively with IBI and 

negatively with SCL (Krumhansl, 1997; Nyklícek et al., 1997). In 

addition, watching the acting performance was also related to significantly 

more music-induced chills. Another recent study showed 

that music-induced chills correlated with increased SCL and HR 

(Guhn, Hamm, & Zentner, 2007). The apparent divergence between 

these previous results and the present findings of increased wonder 

and transcendence associated with decreased IBI and SCL, 

and increased music-induced chills may be explained by differences 

in experimental design and measures. First, previous studies 

used short excerpts from classical orchestral music, whereas we focused 

on opera. Second, the previous studies investigated music 

listening alone, whereas our observations are based on a condition 

that involved music listening while watching the acting performance. 

Third, their conclusions are based on comparisons between 

music expressing negative and positive emotions, identified using 

basic emotions questionnaires. In the present experiment, watching 

the acting performance induced wonder and transcendence 

measured using GEMS. Overall, our results show for the first time 

that watching the acting performance contributes to music-induced 

wonder and transcendence that are associated with decreased 

IBI and SCL, and increased chills. 

In summary, both music listening (compared to baseline), and 

watching the acting performance (compared to music listening) 

decreased IBI and SCL. As shown in Fig. 3, IBI followed the same 

decreasing trend, whereas SCL remained at the same level after 

learning the plot compared to music listening. This means that 

learning the plot did not significantly influence these physiological 

variables, but they nonetheless remained at the level induced by 

music listening (i.e., they did not return to baseline). Therefore, 

music listening decreased RR, IBI, and SCL, learning the plot had 

no effect on these measures, and watching the acting performance 

significantly decreased IBI and SCL again. This indicates that IBI and 

SCL are the main physiological variables that are influenced by music 

listening and watching the acting performance. The only variables 

that were specifically influenced by learning the plot were 

RSA and LF-HRV, which indicates that they are sensitive to the 

addition of meaning in this context. 




4.2. Coherence between subjective and physiological changes 

Table 2 

Correlations between physiological responses, chills, and affect during music listening after learning the plot. 



Manikin 



activation 

Systolic blood pressure (SBP) 0.12 0.1 0.23 0.09 0.24 0.08 0.05 0.01 0.05 0.04 0.01 0.1 

Diastolic blood pressure (DBP) 0.02 0.15 0.00 0.16 0.13 0.39 ** 0.23 0.19 0.11 0.00 0.08 0.05 

Skin conductance level (SCL) 0.02 0.07 0.13 0.09 0.06 0.04 0.18 0.06 0.08 0.02 0.47 ** 0.18 

Respiratory rate (RR) 0.08 0.29 0.33 * 0.42 0.26 0.13 0.1 0.04 0.32 * 0.01 0.01 0.45 ** 

Cardiac interbeat intervals (IBI) 0.09 0.21 0.27 0.17 0.34 * 0.11 0.16 0.04 0.33 * 0.1 0.18 0.09 

Heart rate (HR) 0.05 0.16 0.25 0.13 0.35 * 0.05 0.13 0.02 0.29 0.09 0.22 0.07 

Power in the very low frequency of heart rate variability (VLF-HRV) 0.02 0.23 0.08 0.07 0.02 0.07 0.2 0.15 0.16 0.02 0.13 0.13 

Power in the low frequency of heart rate variability (LF-HRV) 0.36 * 0.02 0.56 ** 0.56 ** 0.46 ** 0.39 * 0.43 ** 0.01 0.47 ** 0.44 ** 0.29 0.35 * 

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.34 * 0.01 0.56 ** 0.56 ** 0.46 ** 0.41 ** 0.43 ** 0.00 0.47 ** 0.42 ** 0.29 0.35 * 

0.16 0.15 0.09 0.14 0.17 0.08 0.07 0.03 0.11 0.00 0.07 0.31 

Ratio between low and high frequency powers of heart rate variability 

(LF/HF) 

Chills 0.34 * 0.03 0.36 * 0.39 * 0.28 0.02 0.27 0.1 0.4 * 0.12 0.36 * 

p 6 0.05. 

p 6 0.01. 

* 

** 

There has been an active emotivist vs. cognitivist debate between 

scholars who argue that music listeners really experience 

emotions, or only identify emotions that music expresses (Kivy, 

1990; Scherer & Zentner, 2001). This study integrated subjective 

and physiological measures of emotional responses, thus adding 

to the developing literature on the psychophysiology of music. In 

this line, a novel and important contribution of the present study 

is that we correlated music-induced emotions measured with a domain-specific 

instrument (i.e., GEMS), with an extensive array of 

emotion-related physiological changes. For instance, we found that 

music-induced wonder positively correlated with RR and chills 

across conditions. Moreover, by comparing the correlations of subjective 

and physiological changes between the three experimental 

conditions, one would observe that the psychophysiological coherence 

increases the most after learning the plot. This might suggest 

that the addition of meaning may be more closely related to the 

coherence between subjective and physiological changes induced 

by music, than the provision of additional sensory information 

(e.g., watching the acting performance). 

4.3. Affective mood and sex 

The present findings that affective mood predicted emotions induced 

by music listening (e.g., power, joyful activation) suggests 

that future studies of music-induced emotions should control for 

this potential confound. Specifically, NA negatively predicted, and 

PA positively predicted power and joyful activation induced by 

music listening. This argues for the role of affective mood in the 

genesis of music-induced emotions, which is also in line with other 

studies (see Kreutz, Ott, Teichmann, Osawa, & Vaitl, 2008). In a recent 

field study (F.R. Baltes, M. Miclea, & A.C. Miu, unpublished 

observations), we have confirmed and extended the relationship 

between the affective mood that the participants reported before 

the beginning of a live opera performance, and the music-induced 

sadness and transcendence (GEMS). This indicates that the influence 

of affective mood is not limited to wonder and transcendence. 

However, the specificity of this association in relation to the musical 

stimuli, and the physical setting (i.e., laboratory vs. field studies) 

might be investigated by future studies. 

We also controlled for sex differences in the present analyses. A 

previous study showed that in comparison to men, women rated 

the chill-producing songs as being sadder (Panksepp, 1995). Another 

study reported that women showed elevated SCL to heavy 

metal compared to Renaissance music (Nater et al., 2006). In light 

of these results, the present study tested the effects of sex, and the 

interaction of sex and musical experience. We expected that after 

learning the plot, and especially during watching the acting performance, 

women would be more reactive due to increased emotional 

empathy with the female character in the musical excerpt. However, 

we found no significant main effect, or interaction of sex with 

musical experience, on subjective or physiological responses. 

4.4. Potential limitations and implications 

One potential limit is that the mere repeated exposure may 

have influenced the present pattern of results. However, this 

possibility was controlled by measuring the same subjective and 

physiological responses while an independent control sample 

re-listened to the same musical excerpt for three times. The results 

from this sample indicated that the emotional arousal and valence, 

the music-induced emotions, or the physiological measures did not 

change with mere re-listening. This is also in line with the studies 

of Grewe et al. (2007a, 2007b). However, we acknowledge that a 

real limitation of the present study comes from the small size of 




Table 3 

Correlations between physiological responses, chills, and affect during music listening while watching the acting performance. 



Manikin 



activation 

Systolic blood pressure (SBP) 0.17 0.18 0.15 0.39 * 0.09 0.2 0.21 0.1 0.09 0.22 0.39 ** 0.02 

Diastolic blood pressure (DBP) 0.13 0.23 0.25 0.32 0.1 0.12 0.04 0.01 0.13 0.1 0.21 0.017 

Skin conductance level (SCL) 0.00 0.16 0.04 0.05 0.09 0.01 0.1 0.05 0.02 0.16 0.1 0.09 

Respiratory rate (RR) 0.32 0.2 0.39 ** 0.49 ** 0.34 * 0.2 0.08 0.01 0.27 0.28 0.22 0.53 ** 

Cardiac interbeat intervals (IBI) 0.17 0.05 0.18 0.25 0.01 0.03 0.01 0.12 0.03 0.21 0.07 0.04 

Heart rate (HR) 0.19 0.00 0.17 0.25 0.04 0.06 0.08 0.16 0.00 0.17 0.02 0.00 

Power in the very low frequency of heart rate variability (VLF-HRV) 0.02 0.00 0.13 0.04 0.12 0.15 0.12 0.25 0.2 0.00 0.13 0.14 

Power in the low frequency of heart rate variability (LF-HRV) 0.08 0.06 0.16 0.1 0.01 0.01 0.11 0.11 0.03 0.00 0.04 0.36 * 

Respiratory sinus arrhythmia (RSA or HF-HRV) 0.02 0.12 0.16 0.1 0.03 0.02 0.11 0.06 0.02 0.12 0.05 0.38 * 

0.05 0.03 0.16 0.22 0.19 0.08 0.07 0.03 0.15 0.06 0.27 0.29 

Ratio between low and high frequency powers of heart rate variability 

(LF/HF) 

Chills 0.2 0.12 0.36 * 0.34 * 0.27 0.12 0.22 0.12 0.28 0.24 0.023 

p 6 0.05. 

p 6 0.01. 

* 

** 

the control sample in comparison to the sample from the main 

experiment. 

In light of the previous literature, musical expertise and (not) 

understanding the original language performance are also unlikely 

to have confounded our results. For instance, Bigand et al. (2005) 

showed that the classification of musical excerpts according to 

the emotional content did not differ between music graduates 

and nonmusicians. Another study found that emotional responses 

are not affected by song translation of non-native original language 

performance (Chiaschi, 2007), such as we did in our third experimental 

condition. It is also unlikely that listening to music with 

eyes open influenced music-induced emotions in the present study 

(Kallinen, 2004). However, future studies might control for personality 

variables (e.g., absorption) that are known to affect emotional 

arousal induced by music (Kreutz et al., 2008). 

These results have theoretical and methodological implications. 

First, they contribute to the literature supporting the emotivist position 

in the psychology of music. Second, they also add evidence in 

favor of the physiological differentiation of emotions. Third, considering 

that psychophysiological measures tended to correlate 

more highly with GEMS scores, and wonder and transcendence 

played a particularly prominent role, the present results emphasize 

the utility of domain-specific instruments to assess music-induced 

emotions. Fourth, many previous studies have paid a high price for 

experimental control, by using sound clips lasting a few seconds 

and crude measures of emotion (Peretz et al., 2001; Vieillard 

et al., 2008). Although these studies contributed to the understanding 

of the minimal conditions that are necessary to express an 

emotional meaning, it remains often unclear whether findings 

from such studies have any bearing on the experience of music 

in real life. Consequently, we chose to use a 19 min excerpt from 

Tosca, edited to contain a coherent plot, in order to realistically 

simulate the real life conditions in which opera induces emotions. 

The rich and complex pattern of psychophysiological results in the 

present study underscores the importance of external validity in 

laboratory studies of music-induced emotions. 

Each experimental condition in the present study manipulated 

an additional variable in relation to the previous conditions (i.e., 

the plot for the second condition, and the visual context for the 

third condition). The rationale behind this type of within-subject 

design is that any change that develops in one condition relative 

to the previous one is determined by the additional variable that 

was manipulated in that condition. However, it is possible that 

rather than being specifically induced by each new variable that 

was manipulated in a certain experimental condition, the changes 

could be due to simply increasing the sensory and semantic complexity 

of the musical experience. For instance, the visual context 

that was added in the third experimental condition might have 

clarified the meaning of the music, or allowed increased depth of 

processing in relation to the first two conditions. Other studies 

have used similar approaches by juxtaposing music and images, 

or lyrics and music, and claimed that emotional changes were specifically 

induced by the variable that differed between conditions 

(e.g., Ali & Peynircioglu, 2006). 

One may wonder whether this pattern of findings might generalize 

to all opera, or is unique to this style of operatic music performance 

(i.e., pertaining to verismo), composer, composition, excerpt, 

or interpretation. Scherer and Zentner (2001) have emphasized 

that music-induced emotions depend on several factors, such as 

structural features of music (i.e., pitch, melody, tempo, rhythm, 

harmony), performance features (e.g., physical appearance, expression, 

reputation, technical and interpretative skills of the performer), 

listener features (e.g., musical expertise, personality, 

affective mood), and contextual features (e.g., location of the 

performance, social framing of the event). The present study 

investigated the influence of affective mood, and controlled for 




important listener features (i.e., musical expertise, familiarity with 

the selected musical piece, preference for classic or operatic music). 

In addition, all the participants listened to the music in the 

same physical setting (i.e., our laboratory). This argues for the generality 

of our findings. It was beyond the purpose of this study to 

investigate the influence of musical structure, and performance 

features. It is likely that the stellar performance of Maria Callas 

and Tito Gobbi in this Tosca performance increased the effectiveness 

of this excerpt in inducing emotions. However, we speculate 

that the pattern of emotions reported here would not have been 

different had we used another interpretation of this opera by artists 

that are vocally and dramatically comparable (or at least 

close) to Maria Callas and Tito Gobbi. Future studies might investigate 

whether these findings can be replicated with excerpts from 

other operas. 

4.5. Conclusion 

In conclusion, this study found that music listening, learning the 

plot, and watching the acting performance had specific effects on 

music-induced emotions and their physiological correlates. Opera 

poses enormous challenges to research due to the multitude of 

musical and dramatic means by which it induces emotions. 

Although the present study only scratched the surface, it opens 

new perspectives for future studies on the mechanisms of musicinduced 

emotions in opera. 

Acknowledgments 

We are grateful to Dr. Laurel J. Trainor and two anonymous 

reviewers for important suggestions that helped us in improving 

the present article, and Dr. Marcel Zentner for permission to use 

the Geneva Emotional Music Scale (GEMS-45) in the study. We also 

thank Silviu Matu for help with data collection. This research was 

supported by the 2010 Arnold Bentley Award from the Society for 

Education, Music, and Psychology (SEMPRE) to R.F.B. and A.C.M., 

and grant 411/2010 from the National University Research Council 

to A.C.M. 

Appendix A. Supplementary material 

Supplementary data associated with this article can be found, in 

the online version, at doi:10.1016/j.bandc.2011.01.012. 

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